connectome_manipulator.connectome_manipulation.manipulation.conn_extraction.ConnectomeExtraction

Connectome manipulation class for extracting connections:

Extracts a subset of connections within a cell target, i.e., keeps only connections within that target and removed all other connections from the connectome. The manipulation can be applied through the apply() method. The nodes (neuron) table is always kept unchanged!

connectome_manipulator.connectome_manipulation.manipulation.conn_extraction.ConnectomeExtraction.apply(self, split_ids, target_name=None, node_sets_file=None, **kwargs)

Applies an extraction of connections within a given cell target.

Parameters:

  • split_ids (list-like) – List of neuron IDs that are part of the current data split; will be automatically provided by the manipulator framework

  • target_name (str) – Cell target name (as defined in SONATA node sets file) to extract connectome from, i.e, keeping only connections within that target; an empty connectome will be returned if no target_name is provided

  • node_sets_file (str) – Optional file path to alternative SONATA node sets file (.json) containing node_id entries; can be provided in case the cell target is not part of the circuit’s intrinsic node sets.

  • **kwargs – Additional keyword arguments - Not used

Note

Input/output edges (synapse) tables are accessed through the writer object:

  • Loading input edges: edges_table = self.writer.to_pandas()

  • Writing output edges: self.writer.from_pandas(edges_table_manip)